The invention relates to time-domain equalization in a discrete multi-tone (DMT) receiver.
Conventional single carrier modulation techniques translate data bits for transmission through a communication channel by varying the amplitude and/or phase of a single sinusoidal carrier. By contrast, DMT, which is also referred to as Orthogonal Frequency Division Multiplexing (OFDM) or Multicarrier Modulation (MCM), employs a large number of sinusoidal subcarriers, e.g., 128 or 256 subcarriers. The available bandwidth of the communication channel is divided into subchannels and each subchannel communicates a part of the data. A DMT system may employ quadrature amplitude modulation (QAM) for each of the subcarriers.
OFDM-based systems transmit blocks of information bits. The time required to transmit one such block is called the symbol period. The time domain waveform that corresponds to one such block of bits is called a symbol.
Intersymbol interference (ISI) arises from the characteristics of practical communication channels and limits the rate at which information can be transmitted through them. Specifically, communication channels typically have an Effective Discrete-Time Impulse Response (EDIR) that is greater than one sample time in length, which causes ISI. ISI is a well-known phenomenon in single-carrier communication systems and there are many techniques for reducing it. The process of such ISI reduction is called equalization. ISI is discussed, for example, in Proakis, Digital Communications, McGraw Hill, 2nd Edition, 1989.
Equalization in OFDM-based systems is achieved by a two stage process. First, at the transmitter, a Cyclic Prefix (CP) is employed by affixing an end-portion of each symbol to the beginning of the symbol. A cyclic prefix that is greater than the EDIR of the channel prevents one symbol from interfering with another. Furthermore, it also facilitates a simple method of neutralizing the time domain spread of each symbol forced by the channel. This is achieved through a simple frequency domain process in the receiver which requires one multiplication operation for each subcarrier used. The use of a Cyclic Prefix to reduce ISI is discussed, for example, in: Cimini, xe2x80x9cAnalysis and Simulation of a Digital Mobile Channel using Orthogonal Frequency Division Multiplexing,xe2x80x9d IEEE Transactions on communications, pp 665-675, July 1985; Chow, xe2x80x9cA Discrete Multi-Tone Transceiver System for HDSL applications,xe2x80x9d IEEE Journal on Selected Areas of Communications, 9(6):895-908, August 1991; and xe2x80x9cDMT Group VDSL PMD Draft Standard Proposal,xe2x80x9d Technical Report, T1E1.4/96-329R2, ANSI 1997.
Another problem arising in conventional DMT systems is noise bleeding, which occurs when noise from one frequency band interferes with a signal whose subcarrier is in another frequency band. Noise bleeding is caused, in general, by a discrete Fourier transform (DFT) operation at the receiver. Noise bleeding is discussed in, for example, Worthen et. al., xe2x80x9cSimulation of VDSL Test Loops,xe2x80x9d Technical Report T1E1.4/97-288, ANSI 1997.
In a perfectly synchronized DMT system, a signal in one frequency band does not interfere with a signal whose subcarrier is in another frequency band. However, noise from one band may interfere with other less noisy bands and render them unusable. Techniques for dealing with noise-bleeding include wavelet-based solutions. However, wavelet-based solutions are, in general, computationally intensive.
Other references dealing with time domain equalization include: Chow, J. S. and Cioffi, J. M., xe2x80x9cA Cost-effective Maximum Likelihood Receiver for Multicarrier Systemsxe2x80x9d, Proceedings of the ICC, 1992; Melsa, Peter J. W., Younce, Richard C., and Rohrs, Charles E., xe2x80x9cOptimal Impulse Response Shorteningxe2x80x9d, Proceedings of the thirty-third Annual Allerton Conference on Communication, Control and Computing, 1995, pp. 431-438; Harikumar, Gopal and Marchok, Daniel, xe2x80x9cShortening the Channel Impulse Response of VDSL Loops for Multicarrier Applicationsxe2x80x9d, Technical report T1E1.4/97-289, ANSI, 1997.
A spectrally constrained impulse shortening filter (SCISF) may be used, for example, in DMT systems. The coefficients of the SCISF may be computed efficiently. For example, the coefficients may be computed and changed through a training process that may occur upon start up of the communication system and periodically during its operation.
The SCISF serves two primary functions. First, it reduces intersymbol interference (ISI) by reducing the length of the effective discrete-time impulse response (EDIR) of the communication channel. Conventional impulse shortening filters may have deep nulls in their frequency response. By contrast, the SCISF has a filter characteristic that is essentially free from undesired nulls that may attenuate or completely eliminate certain subcarriers.
Second, the SCISF reduces noise bleeding between subchannels by attenuating noisy channels in a manner that does not reduce the signal to noise ratio (SNR) in these channels, but reduces the noise power that may appear in the sidelobes of adjacent subchannels. The SCISF accomplishes these functions by applying a frequency constraint to the signal based on a desired spectral response.
The coefficients of the SCISF are computed independent of the length of the cyclic prefix, the symbol length, and the frequency domain equalization characteristics of the system. The SCISF is particularly effective in systems in which additive noise dominates intersymbol interference, or in which noise bleeding predominates. The SCISF reduces noise bleeding with a filter structure that is shorter than that obtained with other techniques. Consequently, the SCISF is less complex and its coefficients are easier to compute, which reduces system complexity and cost. The SCISF may be particularly well suited, for example, for very high-speed digital subscriber lines (VDSL) systems, which generally have low intersymbol interference and tend to suffer from noise bleeding.
In addition, dynamic selection of a cyclic prefix (CP) that maximizes the data throughput for a communication channel having a particular noise profile is provided. Dynamic selection of the CP allows the communication system to adapt to changing noise conditions in the communication channel.
In one aspect, generally, a primary impulse shortening filter is adapted in a multiple carrier communication system. A secondary impulse shortening filter is provided. An output signal of the secondary impulse shortening filter is compared to a reference signal to compute an error signal. Coefficients of the secondary impulse shortening filter are computed in an adaptive processor based on the error signal. Coefficients of the primary impulse shortening filter are replaced with coefficients of the secondary impulse shortening filter.
Embodiments may include one or more of the following features. An output signal of the primary impulse shortening filter may be decoded to form output data. The output data may be encoded to form the reference signal. A discrete Fourier transform may be applied to the output signal of the primary impulse shortening filter prior to decoding the output signal. An inverse discrete Fourier transform may be applied to the encoded output data in forming the reference signal.
A digital signal may be received from an output of an analog to digital converter. The digital signal may be input to the primary impulse shortening filter. The digital signal may be delayed. The delayed digital signal may be input to the secondary impulse shortening filter and the adaptive processor.
The encoded output data may be scaled with a set of scaling factors in forming the reference signal. The scaling factors may be determined by: measuring received noise power spectral density, computing a desired spectral response based on the measured noise power, and computing the scaling factors so that the coefficients computed in the adaptive processor provide the secondary impulse shortening filter with a spectral response that matches the desired spectral response. A discrete Fourier transform may be applied to the output signal of the primary impulse shortening filter prior to decoding the output signal. The noise power spectral density may be measured at an output of the discrete Fourier transform. An inverse discrete Fourier transform may be applied to the scaled, encoded output data.
In another aspect, an impulse shortening filter is adapted in a multiple carrier communication system having a spectrally constrained impulse shortening filter. An output signal of the spectrally constrained impulse shortening filter is compared to a reference signal to compute an error signal. Coefficients of the spectrally constrained impulse shortening filter are computed in an adaptive processor based on the error signal.
Embodiments may include one or more of the following features. The reference signal may be a predetermined signal stored in a memory in the communication system. A discrete Fourier transform may be applied to predetermined reference values to form transformed reference values. The transformed reference values may be scaled with a set of scaling factors to form scaled. An inverse discrete Fourier transform may be applied to the scaled values to form the reference signal.
A data signal may be received from an output of an analog to digital converter. The data signal may be input to the spectrally constrained impulse shortening filter and the adaptive processor.
In another aspect, a multiple carrier communication system includes a primary impulse shortening filter that receives an output signal of an analog to digital converter and accepts coefficients. A secondary impulse shortening filter receives the output signal of the analog to digital converter, outputs an output signal, and passes coefficients to the primary impulse shortening filter. A reference signal generator outputs a reference signal. A comparator compares the output signal and the reference signal and outputs a resulting error signal. An adaptive processor computes coefficients for the secondary impulse shortening filter based on the error signal.
Embodiments may include one or more of the following features. A discrete Fourier transform may receive an output signal of the primary impulse shortening filter. A decoder may receive the transformed output signal from the discrete Fourier transform. The reference signal generator may include an encoder that receives output data from the decoder. The reference signal generator may include a scaling filter that scales the output data from the encoder using a set of scaling factors. An inverse discrete Fourier transform may receive the scaled output signal from the scaling filer.
In another aspect, a multiple carrier communication system may include a spectrally constrained impulse shortening filter that receives an output signal of an analog to digital converter and accepts coefficients. A reference signal generator outputs a reference signal. A comparator compares the output signal and the reference signal and outputs a resulting error signal. An adaptive processor computes coefficients for the spectrally constrained impulse shortening filter based on the error signal.
Embodiments may include one or more of the following features. A memory may store the reference signal as a predetermined signal. A discrete Fourier transform may receive the reference signal from the memory. A scaling filter may scale the reference signal using a set of scaling factors. An inverse discrete Fourier transform may receive the scaled reference signal.
Other features and advantages will be apparent from the following detailed description, including the drawings, and from the claims.